Demand for AI capacity from our family of apps and products has accelerated the growth of our large backbone network. Initially, we expected AI-driven traffic to mainly stay within data centers. However, high replication and data freshness requirements, co-location challenges, and cross-region inference needs have increased traffic by 30-50%. To manage this, we’ve deepened our understanding of the AI traffic lifecycle (from data collection to training / inference) and controlled backbone traffic growth through efficient workload placement, scheduled bulk transfers, and quality of service initiatives. We’ve also had to build larger buffers to future-proof our network. This talk shares our learnings from addressing the surge in AI traffic on our backbone network.